BitTern aims to provide low-cost, high-accuracy post-training ternary quantization tools, as well as 1.58-bit models across diverse architectures, model scales, and reasoning tasks. Its goal is to lower the barrier to entry for developing 1.58-bit models, enabling broader community participation and allowing everyone can contribute and benefit from shared tools and models.
| Project | Venue | Public Release |
|---|---|---|
| CAT-Q | ICML 2026 Oral | Model checkpoints, inference, and evaluation code |
[Stay tuned]We are preparing to release the CAT-Q training code.[22/07/2026]The CAT-Q model checkpoints, inference, and evaluation code are now available.[01/05/2026]🎉🎉🎉CAT-Q: Cost-efficient and Accurate Ternary Quantization for LLMs is accepted to ICML 2026 as an oral.